Linguistic description of external factors and adjustable parameters of the rotort hreshing and separating device

The results of formalizing the problem of pre-setting the parameters of the TORUM axial-rotor type grain harvester when harvesting various agricultural crops are presented. The correct choice of parameters of the working bodies is one of the main conditions for ensuring high quality harvest, which determined the object of this study. The article discusses the implementation of one of the first stages of development of an intelligent information system. Illustrative results of the solutions obtained are presented. The rotary type grain harvester is a complex hierarchical system. Decisions on the values of the adjustable parameters of the combine are made based on the information about the state of environmental factors and parameters of the technical condition of the machine. Taking into account the heterogeneity and vagueness of incoming information, intelligent information systems based on the mathematical apparatus of fuzzy logic are used to make a decision on the choice of values for the parameters of the working parts of the combine. The use of the linguistic approach is due to the complexity and ambiguity of the relationships between regulated parameters and external factors. Models of the considered features in the form of membership functions are proposed. At the same time, basic and extended term sets are defined. An analysis of the consistency of fuzzy expert information in constructing models of task attributes was performed. The consistency of the information presented was analyzed and the optimal models were selected. There has been created a fuzzy knowledge base on which the deductive conclusion of solutions is based. The proposed approach and the created fuzzy knowledge base can be used as the basis for an intelligent decision-making system for customizing the adjustable parameters of a rotary combine. The use of such a system in field conditions in combination with sensors for continuous monitoring of harvesting conditions and an automated image analysis system will allow you to quickly respond to changing conditions, significantly increase work efficiency and reduce decision-making time.